Automated Intelligent Decision Making in Domains With Large Action Spaces

人工智能（AI）研究涉及开发新技术，以便在各种更复杂的现实世界问题中做出智能决策。这个自动化决策制定过程需要对给定的领域进行建模，然后从给定的场景中推断未来可能采取的行动，最终决定采取哪些行动，并考虑到某些目标。人工智能研究人员面临的主要挑战之一是，如何在一个可能的未来场景和行动数量如此之大，以至于无法全部探索的领域中选择采取的行动。据说这些领域有很大的行动空间，其中许多领域需要在几分之一秒内做出实时决策，问题很快就变得棘手了。本提案的主要目标是：更好地理解具有大动作空间的领域的本质，利用这些知识开发新的技术来解决以前过于复杂的领域，并将这些新技术应用于解决现实世界的问题。我未来五年的具体目标是与HQP一起开展研究，研究最初有前景的技术，最终完成4-5名硕士研究生（每个2年）和2名博士研究生（每个4年）的论文。这些短期目标的完成将为长期目标铺平道路，其中包括开发世界级的人工智能系统，以及与加拿大科技行业的合作。近年来，越来越多的人工智能研究人员将电脑游戏和模拟作为开发和测试新人工智能技术的试验台。通过严格的实时计算约束、复杂的规则和模拟现实生活场景的能力，计算机游戏能够在更方便的受控环境中模拟现实世界问题的属性。我计划用电脑游戏作为人工智能最先进技术的试验台。通过严格的实验和数据分析，我希望在启发式搜索、状态抽象、层次分解和降维等领域开发出新颖的技术，这些都是解决这些复杂领域问题所需的关键方法。人工智能正迅速成为我们日常生活中越来越重要的一部分，推动着电子商务、自主机器人、医疗保健和电脑游戏等行业的发展。正如工业革命创造了机器来做我们繁重的工作一样，人工智能革命正在创造机器来做我们繁重的思考。人工智能预计将在未来几年内成为最重要的技术领域之一，这项拟议研究的成功将导致人工智能的进步，这将大大增加加拿大经济的价值，并提高所有加拿大人的整体生活质量。

Artificial Intelligence (AI) research involves the development of new techniques for making intelligent decisions in a wide variety of ever more complex real-world problems. This process of automated decision making requires modelling a given domain, and then reasoning about future actions which are possible from a given scenario, eventually deciding on which action to take with some goal in mind. One of the major challenges faced by AI researchers is how to choose an action to take in a domain where the number of possible future scenarios and actions is so large that there is no way to explore them all. These domains are said to have large action spaces and with many of them requiring real-time decisions to be made in fractions of a second, the problem quickly becomes intractable. The main objectives of this proposal are: to better understand the nature of domains with large action spaces, to use this knowledge to develop novel techniques for tackling domains which were previously too complex, and to apply these new techniques to solve real-world problems. My specific objective for the next five years is to conduct research with HQP to investigate initially promising techniques, resulting in the completed theses for 4-5 MSc students (2 years each), and 2 PhD students (4 years each). The completion of these short-term objectives will pave the way for long term goals which include developing world-class AI systems, and collaboration with the Canadian technology industry.In recent years, an increasing number of AI researchers have been using computer games and simulations as test-beds for developing and testing new AI techniques. With harsh real-time computational constraints, complex rules, and an ability to simulate real-life scenarios, computer games are able to model the properties of real-world problems while being simulated in a more convenient controlled environment. I plan to use computer games as a test-bed for state-of-the-art techniques in AI. Through rigorous experimentation and data analysis, I hope to develop novel techniques in the areas of heuristic search, state abstraction, hierarchical decompositions, and dimensionality reduction, all of which are key methods required for solving problems in these complex domains.AI is quickly becoming an increasing part of our daily lives, powering technologies which advance industries such as e-commerce, autonomous robotics, health care, and computer games. As the industrial revolution created machines to do our heavy lifting, the AI revolution is creating machines to do our heavy thinking. Artificial intelligence is predicted to become one of the most important technology sectors in the next few years, and success in this proposed research will lead to advances in AI which can significantly add value to the Canadian economy, and improve overall quality of life for all Canadians.